Am sure Max of us must be agree or experienced the below challanges in their Digital Journey .
Digital Practices are gaining acceptance especially in the finance and telecom industries however with my experience and in sync with Sr. Executives , there are
plenty RPA failure stories, too. More than 40% of RPA projects fail to deliver expectations in terms of
implementation time
implementation cost
cost savings due to RPA
benefits to analytics
Here I outlined few common pitfalls that lead to these gaps between reality and expectations.
Organizational pitfalls:
1- Lack of time commitment from local team
2- Lack of leadership buy-in
3- Lack of IT support
4- Lack of support from Analytics/Data function
5- Lack of support from HR
6- Unclear responsibilities
7- Company lacking a clear Digital strategy
Process pitfalls:
8- Choosing a process that changes frequently
9- Choosing a process with insignificant business impact
10- Choosing a process where errors are disproportionately costly
11- Choosing a process that involves higher level cognitive tasks
12- Choosing a complex process. Though its sub-processes are simple, process itself may be complex if it has too many sub-processes
13- Choosing a process where better custom solutions exist
14- Striving for end-to-end automation when it is not cost-effective
Implementation pitfalls:
15- Pursuing in-house RPA development with in-house teams that do not have enough capacity
Technical pitfalls:
16- Choosing a solution that requires intensive complicated schnearios.
17- Not relying on availed marketplaces and other readily available tools
18- Choosing a solution that did not demonstrate scalability
Post-implementation pitfalls:
19- Not building for scalability
20- Not taking maintenance needs into account
Digital Practices are gaining acceptance especially in the finance and telecom industries however with my experience and in sync with Sr. Executives , there are
plenty RPA failure stories, too. More than 40% of RPA projects fail to deliver expectations in terms of
implementation time
implementation cost
cost savings due to RPA
benefits to analytics
Here I outlined few common pitfalls that lead to these gaps between reality and expectations.
Organizational pitfalls:
1- Lack of time commitment from local team
2- Lack of leadership buy-in
3- Lack of IT support
4- Lack of support from Analytics/Data function
5- Lack of support from HR
6- Unclear responsibilities
7- Company lacking a clear Digital strategy
Process pitfalls:
8- Choosing a process that changes frequently
9- Choosing a process with insignificant business impact
10- Choosing a process where errors are disproportionately costly
11- Choosing a process that involves higher level cognitive tasks
12- Choosing a complex process. Though its sub-processes are simple, process itself may be complex if it has too many sub-processes
13- Choosing a process where better custom solutions exist
14- Striving for end-to-end automation when it is not cost-effective
Implementation pitfalls:
15- Pursuing in-house RPA development with in-house teams that do not have enough capacity
Technical pitfalls:
16- Choosing a solution that requires intensive complicated schnearios.
17- Not relying on availed marketplaces and other readily available tools
18- Choosing a solution that did not demonstrate scalability
Post-implementation pitfalls:
19- Not building for scalability
20- Not taking maintenance needs into account
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